2020
A Semi-supervised Joint Network for Simultaneous Left Ventricular Motion Tracking and Segmentation in 4D Echocardiography
Ta K, Ahn SS, Stendahl JC, Sinusas AJ, Duncan JS. A Semi-supervised Joint Network for Simultaneous Left Ventricular Motion Tracking and Segmentation in 4D Echocardiography. Lecture Notes In Computer Science 2020, 12266: 468-477. PMID: 33094292, PMCID: PMC7576886, DOI: 10.1007/978-3-030-59725-2_45.Peer-Reviewed Original ResearchA Semi-Supervised Joint Learning Approach to Left Ventricular Segmentation and Motion Tracking in Echocardiography
Ta K, Ahn SS, Lu A, Stendahl JC, Sinusas AJ, Duncan JS. A Semi-Supervised Joint Learning Approach to Left Ventricular Segmentation and Motion Tracking in Echocardiography. 2011 IEEE International Symposium On Biomedical Imaging: From Nano To Macro 2020, 00: 1734-1737. PMID: 33005289, PMCID: PMC7526517, DOI: 10.1109/isbi45749.2020.9098664.Peer-Reviewed Original ResearchMotion trackingUnsupervised motion tracking of left ventricle in echocardiography
Ahn SS, Ta K, Lu A, Stendahl JC, Sinusas AJ, Duncan JS. Unsupervised motion tracking of left ventricle in echocardiography. Proceedings Of SPIE--the International Society For Optical Engineering 2020, 11319: 113190z-113190z-7. PMID: 32994659, PMCID: PMC7521020, DOI: 10.1117/12.2549572.Peer-Reviewed Original ResearchMotion trackingGround truth displacement fieldsConvolutional neural networkAccurate motion trackingDense displacement fieldB-mode echocardiography imagesU-NetNeural networkTracking frameworkNon-rigid registration algorithmTarget imageRegistration algorithmTarget frameSource frameAlgorithmEchocardiography imagesFavorable performanceDatasetImagesTrackingDisplacement estimationLarge amountEchocardiographic imagesSegmentationNetwork
2006
Towards pointwise motion tracking in echocardiographic image sequences – Comparing the reliability of different features for speckle tracking
Yu W, Yan P, Sinusas AJ, Thiele K, Duncan JS. Towards pointwise motion tracking in echocardiographic image sequences – Comparing the reliability of different features for speckle tracking. Medical Image Analysis 2006, 10: 495-508. PMID: 16574465, DOI: 10.1016/j.media.2005.12.003.Peer-Reviewed Original ResearchConceptsMotion trackingBetter compensation resultsRadio frequency signalsLarge deformationDisplacement estimationTissue motionFrequency signalsSmall deformationsRF signalCompensation resultsFiltered featuresTracking featuresDeformationLinear convolution modelExperiment resultsTrackingEchocardiographic image sequencesPhantom examplesReliability measuresImage sequencesB-modeInverse problemSignalsReliabilityDifferent features